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Participation in community programmes by the Roma community is low, whilst this community presents with high risk of poor health and low levels of wellbeing. To improve rates of participation in programmes, compatibility must be achieved between implementation efforts and levels of readiness in the community. The Community Readiness Model (CRM) is a widely used toolkit which provides an indication of how prepared and willing a community is to take action on specific issues. The purpose of this paper is to present findings from a CRM assessment for the Eastern European Roma community in Bradford, UK, on issues related to nutrition and obesity.

The authors interviewed key respondents identified as knowledgeable about the Roma community using the CRM. This approach applies a mixed methodology incorporating readiness scores and qualitative data. A mean community readiness score was calculated enabling researchers to place the community in one of nine possible stages of readiness. Interview transcripts were analysed using a qualitative framework analysis to generate the contextual information.

An overall score consistent with vague awareness was achieved, which indicates a low level of community readiness. This score suggests that there will be a low likelihood of participation in currently available nutrition and obesity programmes.

To our knowledge, this is the first study to apply the CRM in the Roma community for any issue. The authors present the findings for each of the six dimensions that make up the CRM together with salient qualitative findings.

The purpose of this paper is to identify and present a global perspective of digital pedagogies in relation to technology and academic librarians.

The preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology was used in this study.

Based on the data, academic librarians must develop a foundational understanding of 21st century pedagogies and digital skills to teach in an online environment.

This review paper considers the emergent teaching role of the academic librarian within the digital environment. The themes in the findings highlight the importance of digital pedagogical knowledge and digital fluency of academic librarians as a teacher within the digital environment in higher education.

Existing literature on algorithmic management practices – defined as autonomous data-driven decision making in people's management by adoption of self-learning algorithms and artificial intelligence – suggests complex relationships with employees' well-being in the workplace. While the use of algorithms can have positive impacts on people-related decisions, they may also adversely influence job autonomy, perceived justice and – as a result – workplace well-being. Literature review revealed a significant gap in empirical research on the nature and direction of these relationships. Therefore the purpose of this paper is to analyse how algorithmic management practices directly influence workplace well-being, as well as investigating its relationships with job autonomy and total rewards practices.

Conceptual model of relationships between algorithmic management practices, job autonomy, total rewards and workplace well-being has been formulated on the basis of literature review. Proposed model has been empirically verified through confirmatory analysis by means of structural equation modelling (SEM CFA) on a sample of 21,869 European organisations, using data collected by Eurofound and Cedefop in 2019, with the focus of investigating the direct and indirect influence of algorithmic management practices on workplace well-being.

This research confirmed a moderate, direct impact of application of algorithmic management practices on workplace well-being. More importantly the authors found out that this approach has an indirect influence, through negative impact on job autonomy and total rewards practices. The authors observed significant variation in the level of influence depending on the size of the organisation, with the decreasing impacts of algorithmic management on well-being and job autonomy for larger entities.

While the influence of algorithmic management on various workplace practices and effects is now widely discussed, the empirical evidence – especially for traditional work contexts, not only gig economy – is highly limited. The study fills this gap and suggests that algorithmic management – understood as an automated decision-making vehicle – might not always lead to better, well-being focused, people management in organisations. Academic studies and practical applications need to account for possible negative consequences of algorithmic management for the workplace well-being, by better reflecting complex nature of relationships between these variables.